| license: apache-2.0 | |
| tags: | |
| - image-classification | |
| - vision | |
| - generated_from_trainer | |
| datasets: | |
| - cifar10 | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: cifar10_outputs | |
| results: | |
| - task: | |
| name: Image Classification | |
| type: image-classification | |
| dataset: | |
| name: cifar10 | |
| type: cifar10 | |
| args: plain_text | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.991421568627451 | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # cifar10_outputs | |
| This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the cifar10 dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0806 | |
| - Accuracy: 0.9914 | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 0.0001 | |
| - train_batch_size: 17 | |
| - eval_batch_size: 17 | |
| - seed: 1337 | |
| - distributed_type: IPU | |
| - gradient_accumulation_steps: 128 | |
| - total_train_batch_size: 8704 | |
| - total_eval_batch_size: 272 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: cosine | |
| - lr_scheduler_warmup_ratio: 0.25 | |
| - num_epochs: 100.0 | |
| - training precision: Mixed Precision | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.18.0 | |
| - Pytorch 1.10.0+cpu | |
| - Datasets 2.3.3.dev0 | |
| - Tokenizers 0.12.1 | |